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Mamba

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/vison307/mammil

공식 코드

MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models

https://github.com/wailordhe/densessm

공식 코드

DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

https://github.com/wake1021/inceptionmamba

공식 코드

InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck Mamba

https://github.com/walking-shadow/Official_Remote_Sensing_Mamba

공식 코드

RS-Mamba for Large Remote Sensing Image Dense Prediction

https://github.com/wangck20/globalmamba

공식 코드

GlobalMamba: Global Image Serialization for Vision Mamba

https://github.com/wangck20/v2m

공식 코드

V2M: Visual 2-Dimensional Mamba for Image Representation Learning

https://github.com/wangtz19/NetMamba

공식 코드

NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mamba

https://github.com/wangzrk/LMHaze

공식 코드

LMHaze: Intensity-aware Image Dehazing with a Large-scale Multi-intensity Real Haze Dataset

https://github.com/weitunglin/pixmamba

공식 코드

PixMamba: Leveraging State Space Models in a Dual-Level Architecture for Underwater Image Enhancement

https://github.com/weixin-liang/mixture-of-mamba

공식 코드

Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity

https://github.com/wenjuan7275/matir

공식 코드

MatIR: A Hybrid Mamba-Transformer Image Restoration Model

https://github.com/whaleloops/clinicalmamba

공식 코드

ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes

https://github.com/windowso/swim-asad

공식 코드

SWIM: Short-Window CNN Integrated with Mamba for EEG-Based Auditory Spatial Attention Decoding

https://github.com/wjh892521292/lkm-unet

공식 코드

LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation

https://github.com/wjh892521292/lma-unet

공식 코드

LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation

https://github.com/wklix/transma

공식 코드

TransMA: an explainable multi-modal deep learning model for predicting properties of ionizable lipid nanoparticles in mRNA delivery

https://github.com/wongzbb/diffma-diffusion-mamba

공식 코드

Soft Masked Mamba Diffusion Model for CT to MRI Conversion

https://github.com/woominsong/simba

공식 코드

Sparsified State-Space Models are Efficient Highway Networks

https://github.com/wurenkai/UltraLight-VM-UNet

공식 코드

UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation

https://github.com/wurenkai/h-vmunet

공식 코드

H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation

https://github.com/wuyang98/weathergen

공식 코드

WeatherGen: A Unified Diverse Weather Generator for LiDAR Point Clouds via Spider Mamba Diffusion

https://github.com/wuyou3474/mambanut

공식 코드

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning

https://github.com/wuyushuwys/tor_ssm

공식 코드

Rethinking Token Reduction for State Space Models

https://github.com/wxy11-27/gmsr

공식 코드

GMSR:Gradient-Guided Mamba for Spectral Reconstruction from RGB Images

https://github.com/wyd0042/EchoMamba4Rec

공식 코드

EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation

https://github.com/wzhwzhwzh0921/s-d-mamba

공식 코드

Is Mamba Effective for Time Series Forecasting?

https://github.com/xavier-lin/trackssm

공식 코드

TrackSSM: A General Motion Predictor by State-Space Model

https://github.com/xhanxu/Mamba3D

공식 코드

Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model

https://github.com/xi-j/Mamba-TasNet

공식 코드

Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation

https://github.com/xi-j/mamba-asr

공식 코드

Speech Slytherin: Examining the Performance and Efficiency of Mamba for Speech Separation, Recognition, and Synthesis

https://github.com/xian-sh/mol-mamba

공식 코드

MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights

https://github.com/xiangbogaobarry/mambast

공식 코드

MambaST: A Plug-and-Play Cross-Spectral Spatial-Temporal Fuser for Efficient Pedestrian Detection

https://github.com/xiaobul/cm-unet

공식 코드

CM-UNet: Hybrid CNN-Mamba UNet for Remote Sensing Image Semantic Segmentation

https://github.com/xiaojieli0903/mamba-fscil

공식 코드

Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for Few-Shot Class-Incremental Learning

https://github.com/xiaoleiqinn/sitsmamba

공식 코드

SITSMamba for Crop Classification based on Satellite Image Time Series

https://github.com/xiaomenglilili/dh-mamba

공식 코드

DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.